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基于LiDAR点云数据的果树树有效体积计算方法

Hao Ma¹, Kexin Wang¹, Jingyuan Ma¹

¹College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, China.

Frontiers in plant science

|December 4, 2025

概括

这项研究引入了一种使用LiDAR数据计算果树树有效体积 (EV) 的新方法,准确排除多孔性,用于精确的果园管理. 与现有技术相比,EV方法提高了体积预测的准确性.

科学领域:

农业工程农业工程
遥感遥感遥感遥感
林业林业林业林业林业

背景情况:

准确的果树树体积对于精确的果园管理至关重要.
现有的方法通过不考虑树冠多孔性,高估了体积.
立达点云数据为详细的树冠分析提供了潜力.

研究的目的:

利用LiDAR点云数据开发一种用于计算果树树有效体积 (EV) 的新方法.
在体积估计中准确排除树冠多孔性.
为提高精准农业和果园管理战略提供基础.

主要方法:

使用改进的阿尔法形状算法重建果树树冠模型.
开发一个树冠有效体积系数.
计算EV作为重建体积和系数的乘积.
使用模拟和现实世界果园实验进行验证.

主要成果:

拟议的EV方法实现了高精度,R2为0.9720.
优化的参数包括voxel大小等于平均最近邻居距离和分区大小是voxel大小的五倍.
与ASBS (0.5101),CHBS (0.6953) 和VB (0.6213) 方法相比,观察到显著的体积减少率.

结论:

通过去除多孔性,EV方法准确地量化了树冠有效体积.
这种方法为精确的果园管理提供了更好的决策支持.
基于LiDAR的有效体积计算是农业应用的一个可行的进步.

关键词:

李达尔 (LiDAR) 是一种激光雷达.树冠有效体积的有效量.有效体积系数的有效体积系数果树果树果树果树改进了阿尔法形状算法.

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